Integrated metabolomic and transcriptomic study unveils the gene regulatory mechanisms of sugarcane growth promotion during interaction with an endophytic nitrogen-fixing bacteria
Bibliographic record
Abstract
BACKGROUND: Sugarcane growth and yield are complex biological processes influenced by endophytic nitrogen-fixing bacteria, for which the molecular mechanisms involved are largely unknown. In this study, integrated metabolomic and RNA-seq were conducted to investigate the interaction between an endophytic bacterial strain, Burkholderia GXS16, and sugarcane tissue culture seedlings. RESULTS: During treatment, the colonization of GXS16 in sugarcane roots were determined, along with the enhanced activities of various antioxidant enzymes. Accordingly, 161, 113, and 37 differentially accumulated metabolites (DAMs) were found in the pairwise comparisons of adjacent stages. In addition, transcriptomic analyses obtained 1,371 (IN-vs-CN), 1,457 (KN-vs-IN), and 365 (LN-vs-KN) differentially expressed genes (DEGs), which were mainly involved in the pathways of glutathione metabolism and carbon metabolism. We then assessed the pattern of metabolite accumulation and gene expression in sugarcane during GXS16 colonization. The results showed that both DAMs and DGEs in the upregulated expression profiles were involved in the flavonoid biosynthesis pathway. Overall, p-coumaroyl-CoA in sugarcane roots transferred into homoeriodictyol chalcone and 5-deoxyleucopelargonidin due to the upregulation of the expression of genes shikimate O-hydroxycinnamoyltransferase (HCT), chalcone synthase (CHS), and phlorizin synthase (PGT1). CONCLUSIONS: This study provides insights into the gene regulatory mechanisms involved in the interaction between GXS16 and sugarcane roots, which will facilitate future applications of endophytic nitrogen-fixing bacteria to promote crop growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".